Over the past three years, Nvidia has experienced remarkable stock price growth, largely driven by the surging demand for its advanced graphics processing units (GPUs). This rise is not merely speculative; the company has been selling its cutting-edge products almost as quickly as they can be manufactured, thanks to substantial investments from major tech firms in generative artificial intelligence (AI). However, questions linger about whether Nvidia’s $4.4 trillion market cap can continue to expand in the long term.
Recent third-quarter earnings showcased Nvidia’s robust business momentum, with sales soaring 62% year over year to reach $57 billion. A major contributor to this success has been the data center segment, where Nvidia’s advanced GPUs, like Blackwell, are utilized for training and executing AI algorithms. In a bid to sustain this momentum, Nvidia management revealed a next-generation GPU, Rubin, designed to enhance AI video generation capabilities. Set to launch at the end of 2026, Rubin could further fuel growth through 2027 and 2028.
Nvidia benefits from a strong economic moat, fortified by its integration of hardware and software via a programming solution known as CUDA. This familiarity among developers makes switching to competitors challenging, even if alternatives improve in raw performance. The company reported an astonishing gross margin of 73.4% in the third quarter, significantly higher than that of enterprise software giant Microsoft, which has a gross margin around 69%. Such high margins contribute to Nvidia’s substantial profitability, as evidenced by a 65% year-over-year jump in net income to $31.9 billion, bolstering cash available for potential return to investors through share repurchase initiatives.
Despite the positive indicators, investors must consider several risks. Generative AI, while promising, is resource-intensive and costly. For instance, a single query using ChatGPT consumes as much energy as ten Google searches. Nvidia’s substantial pricing for its hardware exacerbates the cost situation, leading significant players in the market to incur steep losses. OpenAI, for example, reported an estimated loss of $11.5 billion last quarter, raising questions about the sustainability of AI hardware demand. This financial strain could incentivize large clients, like OpenAI, to explore economical alternatives. OpenAI is already in the process of developing custom AI chips in collaboration with Broadcom, which would allow them to reduce reliance on Nvidia’s pricier general-purpose hardware while optimizing for specific applications. Other prominent clients, such as Google and Amazon, are also investing in custom chips, posing a potential challenge to Nvidia’s dominance.
Despite these concerns, Nvidia’s fundamentals appear strong for the foreseeable future. Business conditions remain favorable, with a forward price-to-earnings (P/E) ratio of 23, which is lower than the Nasdaq-100’s average estimate of 26. However, the speculative and loss-making nature of generative AI raises caution flags about the sustainability of demand for Nvidia’s products at current levels. Investors may want to consider diversified avenues within the industry for a more balanced approach.
